Knowledge Commons of Institute of Automation,CAS
Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention Localization | |
Wei-Chen Chen; Xin-Yi Yu; Lin-Lin Ou | |
发表期刊 | Machine Intelligence Research
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ISSN | 2731-538X |
2022 | |
卷号 | 19期号:2页码:153-168 |
摘要 | Pedestrian attribute recognition in surveillance scenarios is still a challenging task due to the inaccurate localization of specific attributes. In this paper, we propose a novel view-attribute localization method based on attention (VALA), which utilizes view information to guide the recognition process to focus on specific attributes and attention mechanism to localize specific attribute-corresponding areas. Concretely, view information is leveraged by the view prediction branch to generate four view weights that represent the confidences for attributes from different views. View weights are then delivered back to compose specific view-attributes, which will participate and supervise deep feature extraction. In order to explore the spatial location of a view-attribute, regional attention is introduced to aggregate spatial information and encode inter-channel dependencies of the view feature. Subsequently, a fine attentive attribute-specific region is localized, and regional weights for the view-attribute from different spatial locations are gained by the regional attention. The final view-attribute recognition outcome is obtained by combining the view weights with the regional weights. Experiments on three wide datasets (richly annotated pedestrian (RAP), annotated pedestrian v2 (RAPv2), and PA-100K) demonstrate the effectiveness of our approach compared with state-of-the-art methods. |
关键词 | Pedestrian attribute recognition surveillance scenarios view-attribute attention mechanism localization |
DOI | 10.1007/s11633-022-1321-8 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/55939 |
专题 | 学术期刊_Machine Intelligence Research |
作者单位 | College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China |
推荐引用方式 GB/T 7714 | Wei-Chen Chen,Xin-Yi Yu,Lin-Lin Ou. Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention Localization[J]. Machine Intelligence Research,2022,19(2):153-168. |
APA | Wei-Chen Chen,Xin-Yi Yu,&Lin-Lin Ou.(2022).Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention Localization.Machine Intelligence Research,19(2),153-168. |
MLA | Wei-Chen Chen,et al."Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention Localization".Machine Intelligence Research 19.2(2022):153-168. |
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IJAC-2021-06-150.pdf(1639KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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